Access Restriction

Author Cherkassky, Boris V. ♦ Goldberg, Andrew V. ♦ Martin, Paul ♦ Setubal, Joao C. ♦ Stolfi, Jorge
Source ACM Digital Library
Content type Text
Publisher Association for Computing Machinery (ACM)
File Format PDF
Copyright Year ©1998
Language English
Subject Domain (in DDC) Computer science, information & general works ♦ Computer programming, programs & data
Abstract We conduct a computational study of unit capacity flow and bipartite matching algorithms. Our goal is to determine which variant of the push-relabel method is most efficient in practice and to compare push-relabel algorithms with augmenting path algorithms. We have implemented and compared three push-relabel algorithms, three augmenting-path algorithms (one of which is new), and one augment-relabel algorithm. The depth-first search augmenting path algorithm was thought to be a good choice for the bipartite matching problem, but our study shows that it is not robust (meaning that it is not consistently fast on all or most inputs). For the problems we study, our implementations of the FIFO and lowest-level selection push-relabel algorithms have the most robust asymptotic rate of growth and work best overall. Augmenting path algorithms, although not as robust, on some problem classes are faster by a moderate constant factor. Our study includes several new problem families and input graphs with as many as 5 × $10^{5}$ vertices.
ISSN 10846654
Age Range 18 to 22 years ♦ above 22 year
Educational Use Research
Education Level UG and PG
Learning Resource Type Article
Publisher Date 1998-09-01
Publisher Place New York
e-ISSN 10846654
Journal Journal of Experimental Algorithmics (JEA)
Volume Number 3

Open content in new tab

   Open content in new tab
Source: ACM Digital Library